1. Field
One or more exemplary embodiments relate to a medical image photographing apparatus and a method of processing a medial image, and more particularly, to a medical image photographing apparatus and a method of processing a medical image, which are capable of reducing artifacts in a reconstructed computed tomography (CT) image.
2. Description of the Related Art
Medical imaging apparatuses are used to acquire images showing an internal structure of an object. The medical imaging apparatuses are non-invasive examination devices that capture and process images of details of structures, tissues, flow of fluid, etc., inside a body and provide the images to a user. A user, e.g., a medical practitioner, may use medical images output from the medical imaging apparatuses to diagnose a patient's condition and diseases.
A medical imaging apparatus acquires projection image data by transmitting X-rays through an object, and then reconstructs an image showing a cross-section of an object from the projection image data.
Several reconstruction methods are used during image reconstruction of an object and are classified into two main categories: non-iterative reconstruction and iterative reconstruction techniques.
Non-iterative reconstruction techniques can be divided into direct Fourier reconstruction and back-projection methods, and a back-projection method can be subdivided into filtered back-projection and back-projection filtering. Non-iterative reconstruction methods, other than a direct Fourier reconstruction method, may employ back-projection whereby an image acquired when X-rays propagate through an object and are projected onto an X-ray detector is back-projected into an image reconstruction space.
Iterative reconstruction techniques can be divided into algebraic reconstruction and statistical reconstruction methods. Both the algebraic and statistical reconstruction methods require iterations of a reconstruction process until a desired image is obtained. The process includes comparing an image obtained by projecting a virtual model with a measured image, and comparing an image obtained by modifying the virtual model via back-projection and reprojecting the resulting model with the measured image.
Projection/back-projection algorithms are indispensable for reconstruction of X-ray tomographic images.
In projection or back-projection, the contribution of a detector pixel or a voxel in a voxel grid to the magnitude of an X-ray signal is calculated. Techniques of the related art for calculating the contribution include pixel-driven, ray-driven, and distance-driven approaches. In the pixel-driven approach, a ratio of distances of two detector values from an intersection point between a virtual line passing through a midpoint of each voxel in a voxel grid and a surface of a detector is used as a weighting factor. In the ray-driven approach, a ratio of distances between a virtual line passing through a midpoint of a detector pixel and each of midpoints of two voxels adjacent to the virtual line is defined as a weighting factor. In the distance-driven approach, a ratio of overlapping areas between pixels and voxels projected onto a virtual plane is used as a weighting factor. The pixel-driven, ray-driven, and distance-driven approaches may cause artifacts to occur in a reconstructed image due to properties of a discrete pixel or voxel when calculating weighting factors.
Furthermore, when a C-arm is used as a medical image photographing apparatus, artifacts may be introduced when positions of a detector and an X-ray source finely vary according to a position and an angle of the C-arm.
Thus, it is necessary to reduce artifacts that may occur in a reconstructed image during projection and back-projection in order to improve the quality of the reconstructed image.